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AAMAS
2005
Springer
13 years 10 months ago
Advice-Exchange Between Evolutionary Algorithms and Reinforcement Learning Agents: Experiments in the Pursuit Domain
This research aims at studying the effects of exchanging information during the learning process in Multiagent Systems. The concept of advice-exchange, introduced in (Nunes and Ol...
Luís Nunes, Eugénio C. Oliveira
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
13 years 8 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ATAL
2007
Springer
13 years 10 months ago
Towards reinforcement learning representation transfer
Transfer learning problems are typically framed as leveraging knowledge learned on a source task to improve learning on a related, but different, target task. Current transfer met...
Matthew E. Taylor, Peter Stone
ATAL
2003
Springer
13 years 9 months ago
A selection-mutation model for q-learning in multi-agent systems
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Karl Tuyls, Katja Verbeeck, Tom Lenaerts
EWCBR
2006
Springer
13 years 8 months ago
Multi-agent Case-Based Reasoning for Cooperative Reinforcement Learners
Abstract. In both research fields, Case-Based Reasoning and Reinforcement Learning, the system under consideration gains its expertise from experience. Utilizing this fundamental c...
Thomas Gabel, Martin Riedmiller